moments_normalized
-
skimage.measure.moments_normalized(mu, order=3)
[source] -
Calculate all normalized central image moments up to a certain order.
Note that normalized central moments are translation and scale invariant but not rotation invariant.
Parameters: mu : (M, M) array
Central image moments, where M must be >
order
.order : int, optional
Maximum order of moments. Default is 3.
Returns: nu : (
order + 1
,order + 1
) arrayNormalized central image moments.
References
[R278] Wilhelm Burger, Mark Burge. Principles of Digital Image Processing: Core Algorithms. Springer-Verlag, London, 2009. [R279] B. Jähne. Digital Image Processing. Springer-Verlag, Berlin-Heidelberg, 6. edition, 2005. [R280] T. H. Reiss. Recognizing Planar Objects Using Invariant Image Features, from Lecture notes in computer science, p. 676. Springer, Berlin, 1993. [R281] http://en.wikipedia.org/wiki/Image_moment Examples
1234567891011>>> image
=
np.zeros((
20
,
20
), dtype
=
np.double)
>>> image[
13
:
17
,
13
:
17
]
=
1
>>> m
=
moments(image)
>>> cr
=
m[
0
,
1
]
/
m[
0
,
0
]
>>> cc
=
m[
1
,
0
]
/
m[
0
,
0
]
>>> mu
=
moments_central(image, cr, cc)
>>> moments_normalized(mu)
array([[ nan, nan,
0.078125
,
0.
],
[ nan,
0.
,
0.
,
0.
],
[
0.078125
,
0.
,
0.00610352
,
0.
],
[
0.
,
0.
,
0.
,
0.
]])
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